1.370 000 000 000 000 106 837 Converted to 64 Bit Double Precision IEEE 754 Binary Floating Point Representation Standard

Convert decimal 1.370 000 000 000 000 106 837(10) to 64 bit double precision IEEE 754 binary floating point representation standard (1 bit for sign, 11 bits for exponent, 52 bits for mantissa)

What are the steps to convert decimal number
1.370 000 000 000 000 106 837(10) to 64 bit double precision IEEE 754 binary floating point representation (1 bit for sign, 11 bits for exponent, 52 bits for mantissa)

1. First, convert to binary (in base 2) the integer part: 1.
Divide the number repeatedly by 2.

Keep track of each remainder.

We stop when we get a quotient that is equal to zero.


  • division = quotient + remainder;
  • 1 ÷ 2 = 0 + 1;

2. Construct the base 2 representation of the integer part of the number.

Take all the remainders starting from the bottom of the list constructed above.

1(10) =


1(2)


3. Convert to binary (base 2) the fractional part: 0.370 000 000 000 000 106 837.

Multiply it repeatedly by 2.


Keep track of each integer part of the results.


Stop when we get a fractional part that is equal to zero.


  • #) multiplying = integer + fractional part;
  • 1) 0.370 000 000 000 000 106 837 × 2 = 0 + 0.740 000 000 000 000 213 674;
  • 2) 0.740 000 000 000 000 213 674 × 2 = 1 + 0.480 000 000 000 000 427 348;
  • 3) 0.480 000 000 000 000 427 348 × 2 = 0 + 0.960 000 000 000 000 854 696;
  • 4) 0.960 000 000 000 000 854 696 × 2 = 1 + 0.920 000 000 000 001 709 392;
  • 5) 0.920 000 000 000 001 709 392 × 2 = 1 + 0.840 000 000 000 003 418 784;
  • 6) 0.840 000 000 000 003 418 784 × 2 = 1 + 0.680 000 000 000 006 837 568;
  • 7) 0.680 000 000 000 006 837 568 × 2 = 1 + 0.360 000 000 000 013 675 136;
  • 8) 0.360 000 000 000 013 675 136 × 2 = 0 + 0.720 000 000 000 027 350 272;
  • 9) 0.720 000 000 000 027 350 272 × 2 = 1 + 0.440 000 000 000 054 700 544;
  • 10) 0.440 000 000 000 054 700 544 × 2 = 0 + 0.880 000 000 000 109 401 088;
  • 11) 0.880 000 000 000 109 401 088 × 2 = 1 + 0.760 000 000 000 218 802 176;
  • 12) 0.760 000 000 000 218 802 176 × 2 = 1 + 0.520 000 000 000 437 604 352;
  • 13) 0.520 000 000 000 437 604 352 × 2 = 1 + 0.040 000 000 000 875 208 704;
  • 14) 0.040 000 000 000 875 208 704 × 2 = 0 + 0.080 000 000 001 750 417 408;
  • 15) 0.080 000 000 001 750 417 408 × 2 = 0 + 0.160 000 000 003 500 834 816;
  • 16) 0.160 000 000 003 500 834 816 × 2 = 0 + 0.320 000 000 007 001 669 632;
  • 17) 0.320 000 000 007 001 669 632 × 2 = 0 + 0.640 000 000 014 003 339 264;
  • 18) 0.640 000 000 014 003 339 264 × 2 = 1 + 0.280 000 000 028 006 678 528;
  • 19) 0.280 000 000 028 006 678 528 × 2 = 0 + 0.560 000 000 056 013 357 056;
  • 20) 0.560 000 000 056 013 357 056 × 2 = 1 + 0.120 000 000 112 026 714 112;
  • 21) 0.120 000 000 112 026 714 112 × 2 = 0 + 0.240 000 000 224 053 428 224;
  • 22) 0.240 000 000 224 053 428 224 × 2 = 0 + 0.480 000 000 448 106 856 448;
  • 23) 0.480 000 000 448 106 856 448 × 2 = 0 + 0.960 000 000 896 213 712 896;
  • 24) 0.960 000 000 896 213 712 896 × 2 = 1 + 0.920 000 001 792 427 425 792;
  • 25) 0.920 000 001 792 427 425 792 × 2 = 1 + 0.840 000 003 584 854 851 584;
  • 26) 0.840 000 003 584 854 851 584 × 2 = 1 + 0.680 000 007 169 709 703 168;
  • 27) 0.680 000 007 169 709 703 168 × 2 = 1 + 0.360 000 014 339 419 406 336;
  • 28) 0.360 000 014 339 419 406 336 × 2 = 0 + 0.720 000 028 678 838 812 672;
  • 29) 0.720 000 028 678 838 812 672 × 2 = 1 + 0.440 000 057 357 677 625 344;
  • 30) 0.440 000 057 357 677 625 344 × 2 = 0 + 0.880 000 114 715 355 250 688;
  • 31) 0.880 000 114 715 355 250 688 × 2 = 1 + 0.760 000 229 430 710 501 376;
  • 32) 0.760 000 229 430 710 501 376 × 2 = 1 + 0.520 000 458 861 421 002 752;
  • 33) 0.520 000 458 861 421 002 752 × 2 = 1 + 0.040 000 917 722 842 005 504;
  • 34) 0.040 000 917 722 842 005 504 × 2 = 0 + 0.080 001 835 445 684 011 008;
  • 35) 0.080 001 835 445 684 011 008 × 2 = 0 + 0.160 003 670 891 368 022 016;
  • 36) 0.160 003 670 891 368 022 016 × 2 = 0 + 0.320 007 341 782 736 044 032;
  • 37) 0.320 007 341 782 736 044 032 × 2 = 0 + 0.640 014 683 565 472 088 064;
  • 38) 0.640 014 683 565 472 088 064 × 2 = 1 + 0.280 029 367 130 944 176 128;
  • 39) 0.280 029 367 130 944 176 128 × 2 = 0 + 0.560 058 734 261 888 352 256;
  • 40) 0.560 058 734 261 888 352 256 × 2 = 1 + 0.120 117 468 523 776 704 512;
  • 41) 0.120 117 468 523 776 704 512 × 2 = 0 + 0.240 234 937 047 553 409 024;
  • 42) 0.240 234 937 047 553 409 024 × 2 = 0 + 0.480 469 874 095 106 818 048;
  • 43) 0.480 469 874 095 106 818 048 × 2 = 0 + 0.960 939 748 190 213 636 096;
  • 44) 0.960 939 748 190 213 636 096 × 2 = 1 + 0.921 879 496 380 427 272 192;
  • 45) 0.921 879 496 380 427 272 192 × 2 = 1 + 0.843 758 992 760 854 544 384;
  • 46) 0.843 758 992 760 854 544 384 × 2 = 1 + 0.687 517 985 521 709 088 768;
  • 47) 0.687 517 985 521 709 088 768 × 2 = 1 + 0.375 035 971 043 418 177 536;
  • 48) 0.375 035 971 043 418 177 536 × 2 = 0 + 0.750 071 942 086 836 355 072;
  • 49) 0.750 071 942 086 836 355 072 × 2 = 1 + 0.500 143 884 173 672 710 144;
  • 50) 0.500 143 884 173 672 710 144 × 2 = 1 + 0.000 287 768 347 345 420 288;
  • 51) 0.000 287 768 347 345 420 288 × 2 = 0 + 0.000 575 536 694 690 840 576;
  • 52) 0.000 575 536 694 690 840 576 × 2 = 0 + 0.001 151 073 389 381 681 152;
  • 53) 0.001 151 073 389 381 681 152 × 2 = 0 + 0.002 302 146 778 763 362 304;

We didn't get any fractional part that was equal to zero. But we had enough iterations (over Mantissa limit) and at least one integer that was different from zero => FULL STOP (Losing precision - the converted number we get in the end will be just a very good approximation of the initial one).


4. Construct the base 2 representation of the fractional part of the number.

Take all the integer parts of the multiplying operations, starting from the top of the constructed list above:


0.370 000 000 000 000 106 837(10) =


0.0101 1110 1011 1000 0101 0001 1110 1011 1000 0101 0001 1110 1100 0(2)

5. Positive number before normalization:

1.370 000 000 000 000 106 837(10) =


1.0101 1110 1011 1000 0101 0001 1110 1011 1000 0101 0001 1110 1100 0(2)

6. Normalize the binary representation of the number.

Shift the decimal mark 0 positions to the left, so that only one non zero digit remains to the left of it:


1.370 000 000 000 000 106 837(10) =


1.0101 1110 1011 1000 0101 0001 1110 1011 1000 0101 0001 1110 1100 0(2) =


1.0101 1110 1011 1000 0101 0001 1110 1011 1000 0101 0001 1110 1100 0(2) × 20


7. Up to this moment, there are the following elements that would feed into the 64 bit double precision IEEE 754 binary floating point representation:

Sign 0 (a positive number)


Exponent (unadjusted): 0


Mantissa (not normalized):
1.0101 1110 1011 1000 0101 0001 1110 1011 1000 0101 0001 1110 1100 0


8. Adjust the exponent.

Use the 11 bit excess/bias notation:


Exponent (adjusted) =


Exponent (unadjusted) + 2(11-1) - 1 =


0 + 2(11-1) - 1 =


(0 + 1 023)(10) =


1 023(10)


9. Convert the adjusted exponent from the decimal (base 10) to 11 bit binary.

Use the same technique of repeatedly dividing by 2:


  • division = quotient + remainder;
  • 1 023 ÷ 2 = 511 + 1;
  • 511 ÷ 2 = 255 + 1;
  • 255 ÷ 2 = 127 + 1;
  • 127 ÷ 2 = 63 + 1;
  • 63 ÷ 2 = 31 + 1;
  • 31 ÷ 2 = 15 + 1;
  • 15 ÷ 2 = 7 + 1;
  • 7 ÷ 2 = 3 + 1;
  • 3 ÷ 2 = 1 + 1;
  • 1 ÷ 2 = 0 + 1;

10. Construct the base 2 representation of the adjusted exponent.

Take all the remainders starting from the bottom of the list constructed above.


Exponent (adjusted) =


1023(10) =


011 1111 1111(2)


11. Normalize the mantissa.

a) Remove the leading (the leftmost) bit, since it's allways 1, and the decimal point, if the case.


b) Adjust its length to 52 bits, by removing the excess bits, from the right (if any of the excess bits is set on 1, we are losing precision...).


Mantissa (normalized) =


1. 0101 1110 1011 1000 0101 0001 1110 1011 1000 0101 0001 1110 1100 0 =


0101 1110 1011 1000 0101 0001 1110 1011 1000 0101 0001 1110 1100


12. The three elements that make up the number's 64 bit double precision IEEE 754 binary floating point representation:

Sign (1 bit) =
0 (a positive number)


Exponent (11 bits) =
011 1111 1111


Mantissa (52 bits) =
0101 1110 1011 1000 0101 0001 1110 1011 1000 0101 0001 1110 1100


Decimal number 1.370 000 000 000 000 106 837 converted to 64 bit double precision IEEE 754 binary floating point representation:

0 - 011 1111 1111 - 0101 1110 1011 1000 0101 0001 1110 1011 1000 0101 0001 1110 1100

How to convert numbers from the decimal system (base ten) to 64 bit double precision IEEE 754 binary floating point standard

Follow the steps below to convert a base 10 decimal number to 64 bit double precision IEEE 754 binary floating point:

  • 1. If the number to be converted is negative, start with its the positive version.
  • 2. First convert the integer part. Divide repeatedly by 2 the positive representation of the integer number that is to be converted to binary, until we get a quotient that is equal to zero, keeping track of each remainder.
  • 3. Construct the base 2 representation of the positive integer part of the number, by taking all the remainders from the previous operations, starting from the bottom of the list constructed above. Thus, the last remainder of the divisions becomes the first symbol (the leftmost) of the base two number, while the first remainder becomes the last symbol (the rightmost).
  • 4. Then convert the fractional part. Multiply the number repeatedly by 2, until we get a fractional part that is equal to zero, keeping track of each integer part of the results.
  • 5. Construct the base 2 representation of the fractional part of the number, by taking all the integer parts of the multiplying operations, starting from the top of the list constructed above (they should appear in the binary representation, from left to right, in the order they have been calculated).
  • 6. Normalize the binary representation of the number, shifting the decimal mark (the decimal point) "n" positions either to the left, or to the right, so that only one non zero digit remains to the left of the decimal mark.
  • 7. Adjust the exponent in 11 bit excess/bias notation and then convert it from decimal (base 10) to 11 bit binary, by using the same technique of repeatedly dividing by 2, as shown above:
    Exponent (adjusted) = Exponent (unadjusted) + 2(11-1) - 1
  • 8. Normalize mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal mark, if the case) and adjust its length to 52 bits, either by removing the excess bits from the right (losing precision...) or by adding extra bits set on '0' to the right.
  • 9. Sign (it takes 1 bit) is either 1 for a negative or 0 for a positive number.

Example: convert the negative number -31.640 215 from the decimal system (base ten) to 64 bit double precision IEEE 754 binary floating point:

  • 1. Start with the positive version of the number:

    |-31.640 215| = 31.640 215

  • 2. First convert the integer part, 31. Divide it repeatedly by 2, keeping track of each remainder, until we get a quotient that is equal to zero:
    • division = quotient + remainder;
    • 31 ÷ 2 = 15 + 1;
    • 15 ÷ 2 = 7 + 1;
    • 7 ÷ 2 = 3 + 1;
    • 3 ÷ 2 = 1 + 1;
    • 1 ÷ 2 = 0 + 1;
    • We have encountered a quotient that is ZERO => FULL STOP
  • 3. Construct the base 2 representation of the integer part of the number by taking all the remainders of the previous dividing operations, starting from the bottom of the list constructed above:

    31(10) = 1 1111(2)

  • 4. Then, convert the fractional part, 0.640 215. Multiply repeatedly by 2, keeping track of each integer part of the results, until we get a fractional part that is equal to zero:
    • #) multiplying = integer + fractional part;
    • 1) 0.640 215 × 2 = 1 + 0.280 43;
    • 2) 0.280 43 × 2 = 0 + 0.560 86;
    • 3) 0.560 86 × 2 = 1 + 0.121 72;
    • 4) 0.121 72 × 2 = 0 + 0.243 44;
    • 5) 0.243 44 × 2 = 0 + 0.486 88;
    • 6) 0.486 88 × 2 = 0 + 0.973 76;
    • 7) 0.973 76 × 2 = 1 + 0.947 52;
    • 8) 0.947 52 × 2 = 1 + 0.895 04;
    • 9) 0.895 04 × 2 = 1 + 0.790 08;
    • 10) 0.790 08 × 2 = 1 + 0.580 16;
    • 11) 0.580 16 × 2 = 1 + 0.160 32;
    • 12) 0.160 32 × 2 = 0 + 0.320 64;
    • 13) 0.320 64 × 2 = 0 + 0.641 28;
    • 14) 0.641 28 × 2 = 1 + 0.282 56;
    • 15) 0.282 56 × 2 = 0 + 0.565 12;
    • 16) 0.565 12 × 2 = 1 + 0.130 24;
    • 17) 0.130 24 × 2 = 0 + 0.260 48;
    • 18) 0.260 48 × 2 = 0 + 0.520 96;
    • 19) 0.520 96 × 2 = 1 + 0.041 92;
    • 20) 0.041 92 × 2 = 0 + 0.083 84;
    • 21) 0.083 84 × 2 = 0 + 0.167 68;
    • 22) 0.167 68 × 2 = 0 + 0.335 36;
    • 23) 0.335 36 × 2 = 0 + 0.670 72;
    • 24) 0.670 72 × 2 = 1 + 0.341 44;
    • 25) 0.341 44 × 2 = 0 + 0.682 88;
    • 26) 0.682 88 × 2 = 1 + 0.365 76;
    • 27) 0.365 76 × 2 = 0 + 0.731 52;
    • 28) 0.731 52 × 2 = 1 + 0.463 04;
    • 29) 0.463 04 × 2 = 0 + 0.926 08;
    • 30) 0.926 08 × 2 = 1 + 0.852 16;
    • 31) 0.852 16 × 2 = 1 + 0.704 32;
    • 32) 0.704 32 × 2 = 1 + 0.408 64;
    • 33) 0.408 64 × 2 = 0 + 0.817 28;
    • 34) 0.817 28 × 2 = 1 + 0.634 56;
    • 35) 0.634 56 × 2 = 1 + 0.269 12;
    • 36) 0.269 12 × 2 = 0 + 0.538 24;
    • 37) 0.538 24 × 2 = 1 + 0.076 48;
    • 38) 0.076 48 × 2 = 0 + 0.152 96;
    • 39) 0.152 96 × 2 = 0 + 0.305 92;
    • 40) 0.305 92 × 2 = 0 + 0.611 84;
    • 41) 0.611 84 × 2 = 1 + 0.223 68;
    • 42) 0.223 68 × 2 = 0 + 0.447 36;
    • 43) 0.447 36 × 2 = 0 + 0.894 72;
    • 44) 0.894 72 × 2 = 1 + 0.789 44;
    • 45) 0.789 44 × 2 = 1 + 0.578 88;
    • 46) 0.578 88 × 2 = 1 + 0.157 76;
    • 47) 0.157 76 × 2 = 0 + 0.315 52;
    • 48) 0.315 52 × 2 = 0 + 0.631 04;
    • 49) 0.631 04 × 2 = 1 + 0.262 08;
    • 50) 0.262 08 × 2 = 0 + 0.524 16;
    • 51) 0.524 16 × 2 = 1 + 0.048 32;
    • 52) 0.048 32 × 2 = 0 + 0.096 64;
    • 53) 0.096 64 × 2 = 0 + 0.193 28;
    • We didn't get any fractional part that was equal to zero. But we had enough iterations (over Mantissa limit = 52) and at least one integer part that was different from zero => FULL STOP (losing precision...).
  • 5. Construct the base 2 representation of the fractional part of the number, by taking all the integer parts of the previous multiplying operations, starting from the top of the constructed list above:

    0.640 215(10) = 0.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2)

  • 6. Summarizing - the positive number before normalization:

    31.640 215(10) = 1 1111.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2)

  • 7. Normalize the binary representation of the number, shifting the decimal mark 4 positions to the left so that only one non-zero digit stays to the left of the decimal mark:

    31.640 215(10) =
    1 1111.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2) =
    1 1111.1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2) × 20 =
    1.1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0(2) × 24

  • 8. Up to this moment, there are the following elements that would feed into the 64 bit double precision IEEE 754 binary floating point representation:

    Sign: 1 (a negative number)

    Exponent (unadjusted): 4

    Mantissa (not-normalized): 1.1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0

  • 9. Adjust the exponent in 11 bit excess/bias notation and then convert it from decimal (base 10) to 11 bit binary (base 2), by using the same technique of repeatedly dividing it by 2, as shown above:

    Exponent (adjusted) = Exponent (unadjusted) + 2(11-1) - 1 = (4 + 1023)(10) = 1027(10) =
    100 0000 0011(2)

  • 10. Normalize mantissa, remove the leading (leftmost) bit, since it's allways '1' (and the decimal sign) and adjust its length to 52 bits, by removing the excess bits, from the right (losing precision...):

    Mantissa (not-normalized): 1.1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100 1010 0

    Mantissa (normalized): 1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100

  • Conclusion:

    Sign (1 bit) = 1 (a negative number)

    Exponent (8 bits) = 100 0000 0011

    Mantissa (52 bits) = 1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100

  • Number -31.640 215, converted from decimal system (base 10) to 64 bit double precision IEEE 754 binary floating point =
    1 - 100 0000 0011 - 1111 1010 0011 1110 0101 0010 0001 0101 0111 0110 1000 1001 1100